Improve schedule quality feature (#1602)
# What this PR does Before: <img width="281" alt="Screenshot 2023-03-23 at 16 56 42" src="https://user-images.githubusercontent.com/20116910/227279464-c883ec05-a964-4360-bda2-3443409ca90a.png"> After: <img width="338" alt="Screenshot 2023-03-23 at 16 57 41" src="https://user-images.githubusercontent.com/20116910/227279476-468bffba-922a-45ea-b400-5f34d6bf0534.png"> - Add scores for overloaded users, e.g. `(+25% avg)` which means the user is scheduled to be on-call 25% more than average for given schedule. - Add score for gaps, e.g. `Schedule has gaps (29% not covered)` which means 29% of time no one is scheduled to be on-call. - Make things easier to understand when there are gaps in the schedule, add `(see overloaded users)` text. - Consider events for next 52 weeks (~1 year) instead of 90 days (~3 months), so the quality report is more accurate. Also treat any balance quality >95% as perfectly balanced. These two changes (period change and adding 95% threshold) should help eliminate false positives for _most_ schedules. - Modify backend & frontend so the backend returns all necessary user information to render without using the user store. - Move quality report generation to `OnCallSchedule` model, add more tests. ## Which issue(s) this PR fixes Related to https://github.com/grafana/oncall/issues/1552 ## Checklist - [x] Tests updated - [x] `CHANGELOG.md` updated (public docs will be added in a separate PR)
This commit is contained in:
Vadim Stepanov
GitHub
parent
a2caeae3c7
commit
a936c8c7fe
10 changed files with 430 additions and 179 deletions
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@ -14,6 +14,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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using URLs without a top-level domain ([1266](https://github.com/grafana/oncall/pull/1266))
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- Updated wording when creating an integration ([1572](https://github.com/grafana/oncall/pull/1572))
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- Set FCM iOS/Android "message priority" to "high priority" for mobile app push notifications ([1612](https://github.com/grafana/oncall/pull/1612))
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- Improve schedule quality feature (by @vadimkerr in [#1602](https://github.com/grafana/oncall/pull/1602))
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### Fixed
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@ -27,7 +27,6 @@ from apps.auth_token.auth import PluginAuthentication
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from apps.auth_token.constants import SCHEDULE_EXPORT_TOKEN_NAME
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from apps.auth_token.models import ScheduleExportAuthToken
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from apps.schedules.models import OnCallSchedule
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from apps.schedules.quality_score import get_schedule_quality_score
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from apps.slack.models import SlackChannel
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from apps.slack.tasks import update_slack_user_group_for_schedules
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from common.api_helpers.exceptions import BadRequest, Conflict
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@ -353,13 +352,12 @@ class ScheduleView(
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@action(detail=True, methods=["get"])
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def quality(self, request, pk):
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schedule = self.get_object()
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user_tz, date = self.get_request_timezone()
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days = int(self.request.query_params.get("days", 90)) # todo: check if days could be calculated more precisely
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events = schedule.filter_events(user_tz, date, days=days, with_empty=True, with_gap=True)
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_, date = self.get_request_timezone()
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days = self.request.query_params.get("days")
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days = int(days) if days else None
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schedule_score = get_schedule_quality_score(events, days)
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return Response(schedule_score)
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return Response(schedule.quality_report(date, days))
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@action(detail=False, methods=["get"])
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def type_options(self, request):
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@ -1,6 +1,9 @@
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import datetime
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import functools
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import itertools
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from collections import defaultdict
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from enum import Enum
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from typing import Iterable, Optional, TypedDict
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import icalendar
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import pytz
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@ -23,9 +26,33 @@ from apps.schedules.ical_utils import (
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list_of_oncall_shifts_from_ical,
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)
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from apps.schedules.models import CustomOnCallShift
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from apps.user_management.models import User
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from common.public_primary_keys import generate_public_primary_key, increase_public_primary_key_length
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# Utility classes for schedule quality report
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class QualityReportCommentType(str, Enum):
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INFO = "info"
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WARNING = "warning"
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class QualityReportComment(TypedDict):
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type: QualityReportCommentType
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text: str
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class QualityReportOverloadedUser(TypedDict):
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id: str
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username: str
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score: int
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class QualityReport(TypedDict):
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total_score: int
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comments: list[QualityReportComment]
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overloaded_users: list[QualityReportOverloadedUser]
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def generate_public_primary_key_for_oncall_schedule_channel():
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prefix = "S"
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new_public_primary_key = generate_public_primary_key(prefix)
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@ -256,6 +283,126 @@ class OnCallSchedule(PolymorphicModel):
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events = self._resolve_schedule(events)
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return events
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def quality_report(self, date: Optional[timezone.datetime], days: Optional[int]) -> QualityReport:
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"""
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Return schedule quality report to be used by the web UI.
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TODO: Add scores on "inside working hours" and "balance outside working hours" when
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TODO: working hours editor is implemented in the web UI.
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"""
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# get events to consider for calculation
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if date is None:
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today = datetime.datetime.now(tz=datetime.timezone.utc)
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date = today - datetime.timedelta(days=7 - today.weekday()) # start of next week in UTC
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if days is None:
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days = 52 * 7 # consider next 52 weeks (~1 year)
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events = self.final_events(user_tz="UTC", starting_date=date, days=days)
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# an event is “good” if it's not a gap and not empty
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good_events = [event for event in events if not event["is_gap"] and not event["is_empty"]]
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if not good_events:
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return {
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"total_score": 0,
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"comments": [{"type": QualityReportCommentType.WARNING, "text": "Schedule is empty"}],
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"overloaded_users": [],
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}
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def event_duration(ev: dict) -> datetime.timedelta:
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return ev["end"] - ev["start"]
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def timedelta_sum(deltas: Iterable[datetime.timedelta]) -> datetime.timedelta:
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return sum(deltas, start=datetime.timedelta())
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def score_to_percent(value: float) -> int:
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return round(value * 100)
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def get_duration_map(evs: list[dict]) -> dict[str, datetime.timedelta]:
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"""Return a map of user PKs to total duration of events they are in."""
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result = defaultdict(datetime.timedelta)
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for ev in evs:
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for user in ev["users"]:
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user_pk = user["pk"]
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result[user_pk] += event_duration(ev)
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return result
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def get_balance_score_by_duration_map(dur_map: dict[str, datetime.timedelta]) -> float:
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"""
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Return a score between 0 and 1, based on how balanced the durations are in the duration map.
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The formula is taken from https://github.com/grafana/oncall/issues/118#issuecomment-1161787854.
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"""
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if len(dur_map) <= 1:
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return 1
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result = 0
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for key_1, key_2 in itertools.combinations(dur_map, 2):
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duration_1 = dur_map[key_1]
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duration_2 = dur_map[key_2]
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result += min(duration_1, duration_2) / max(duration_1, duration_2)
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number_of_pairs = len(dur_map) * (len(dur_map) - 1) // 2
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return result / number_of_pairs
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# calculate good event score
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good_events_duration = timedelta_sum(event_duration(event) for event in good_events)
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good_event_score = min(good_events_duration / datetime.timedelta(days=days), 1)
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good_event_score = score_to_percent(good_event_score)
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# calculate balance score
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duration_map = get_duration_map(good_events)
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balance_score = get_balance_score_by_duration_map(duration_map)
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balance_score = score_to_percent(balance_score)
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# calculate overloaded users
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if balance_score >= 95: # tolerate minor imbalance
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balance_score = 100
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overloaded_users = []
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else:
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average_duration = timedelta_sum(duration_map.values()) / len(duration_map)
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overloaded_user_pks = [user_pk for user_pk, duration in duration_map.items() if duration > average_duration]
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usernames = {
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u.public_primary_key: u.username
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for u in User.objects.filter(public_primary_key__in=overloaded_user_pks).only(
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"public_primary_key", "username"
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)
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}
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overloaded_users = []
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for user_pk in overloaded_user_pks:
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score = score_to_percent(duration_map[user_pk] / average_duration) - 100
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username = usernames.get(user_pk) or "unknown" # fallback to "unknown" if user is not found
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overloaded_users.append({"id": user_pk, "username": username, "score": score})
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# show most overloaded users first
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overloaded_users.sort(key=lambda u: (-u["score"], u["username"]))
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# generate comments regarding gaps
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comments = []
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if good_event_score == 100:
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comments.append({"type": QualityReportCommentType.INFO, "text": "Schedule has no gaps"})
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else:
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not_covered = 100 - good_event_score
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comments.append(
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{"type": QualityReportCommentType.WARNING, "text": f"Schedule has gaps ({not_covered}% not covered)"}
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)
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# generate comments regarding balance
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if balance_score == 100:
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comments.append({"type": QualityReportCommentType.INFO, "text": "Schedule is perfectly balanced"})
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else:
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comments.append(
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{"type": QualityReportCommentType.WARNING, "text": "Schedule has balance issues (see overloaded users)"}
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)
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# calculate total score (weighted sum of good event score and balance score)
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total_score = round((good_event_score + balance_score) / 2)
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return {
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"total_score": total_score,
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"comments": comments,
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"overloaded_users": overloaded_users,
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}
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def _resolve_schedule(self, events):
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"""Calculate final schedule shifts considering rotations and overrides."""
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if not events:
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@ -1,117 +0,0 @@
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import datetime
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import enum
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import itertools
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from collections import defaultdict
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from typing import Iterable, Union
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import pytz
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class CommentType(str, enum.Enum):
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INFO = "info"
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WARNING = "warning"
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# TODO: add "inside working hours score" and "balance outside working hours score" when working hours editor is implemented
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def get_schedule_quality_score(events: list[dict], days: int) -> dict:
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# an event is “good” if it's a primary event, not a gap and not empty
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good_events = [
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event for event in events if not event["is_override"] and not event["is_gap"] and not event["is_empty"]
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]
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good_event_score = get_good_event_score(good_events, days)
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# formula for balance score is taken from here: https://github.com/grafana/oncall/issues/118
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balance_score, overloaded_users = get_balance_score(good_events)
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if events:
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total_score = (good_event_score + balance_score) / 2
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else:
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total_score = 0
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comments = []
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if good_event_score < 1:
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comments.append({"type": CommentType.WARNING, "text": "Schedule has gaps"})
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else:
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comments.append({"type": CommentType.INFO, "text": "Schedule has no gaps"})
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if balance_score < 0.8:
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comments.append({"type": CommentType.WARNING, "text": "Schedule has balance issues"})
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elif 0.8 <= balance_score < 1:
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comments.append({"type": CommentType.INFO, "text": "Schedule is well-balanced, but still can be improved"})
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else:
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comments.append({"type": CommentType.INFO, "text": "Schedule is perfectly balanced"})
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return {
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"total_score": score_to_percent(total_score),
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"comments": comments,
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"overloaded_users": overloaded_users,
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}
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def get_good_event_score(good_events: list[dict], days: int) -> float:
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good_events_duration = timedelta_sum(event_duration(event) for event in good_events)
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good_event_score = min(
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good_events_duration / datetime.timedelta(days=days), 1
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) # todo: deal with overlapping events
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return good_event_score
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def get_balance_score(events: list[dict]) -> tuple[float, list[str]]:
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duration_map = defaultdict(datetime.timedelta)
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for event in events:
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for user in event["users"]:
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user_pk = user["pk"]
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duration_map[user_pk] += event_duration(event)
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if len(duration_map) == 0:
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return 1, []
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average_duration = timedelta_sum(duration_map.values()) / len(duration_map)
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overloaded_users = [user_pk for user_pk, duration in duration_map.items() if duration > average_duration]
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return get_balance_score_by_duration_map(duration_map), overloaded_users
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def get_balance_score_by_duration_map(duration_map: dict[str, datetime.timedelta]) -> float:
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if len(duration_map) <= 1:
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return 1
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score = 0
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for key_1, key_2 in itertools.combinations(duration_map, 2):
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duration_1 = duration_map[key_1]
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duration_2 = duration_map[key_2]
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score += min(duration_1, duration_2) / max(duration_1, duration_2)
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number_of_pairs = len(duration_map) * (len(duration_map) - 1) // 2
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balance_score = score / number_of_pairs
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return balance_score
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def get_day_start(dt: Union[datetime.datetime, datetime.date]) -> datetime.datetime:
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return datetime.datetime.combine(dt, datetime.datetime.min.time(), tzinfo=pytz.UTC)
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def get_day_end(dt: Union[datetime.datetime, datetime.date]) -> datetime.datetime:
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return datetime.datetime.combine(dt, datetime.datetime.max.time(), tzinfo=pytz.UTC)
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def event_duration(event: dict) -> datetime.timedelta:
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start = event["start"]
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end = event["end"]
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if event["all_day"]:
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start = get_day_start(start)
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# adding one microsecond to the end datetime to make sure 1 day-long events are really 1 day long
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end = get_day_end(end) + datetime.timedelta(microseconds=1)
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return end - start
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def timedelta_sum(deltas: Iterable[datetime.timedelta]) -> datetime.timedelta:
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return sum(deltas, start=datetime.timedelta())
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def score_to_percent(score: float) -> int:
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return round(score * 100)
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@ -1,10 +1,12 @@
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import datetime
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import pytest
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from rest_framework import status
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from rest_framework.reverse import reverse
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from rest_framework.test import APIClient
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from apps.schedules.ical_utils import memoized_users_in_ical
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from apps.schedules.models import OnCallScheduleICal
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from apps.schedules.models import CustomOnCallShift, OnCallScheduleICal, OnCallScheduleWeb
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@pytest.fixture
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@ -54,8 +56,7 @@ def test_get_schedule_score_no_events(get_schedule_quality_response):
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assert response.json() == {
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"total_score": 0,
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"comments": [
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{"type": "warning", "text": "Schedule has gaps"},
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{"type": "info", "text": "Schedule is perfectly balanced"},
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{"type": "warning", "text": "Schedule is empty"},
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],
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"overloaded_users": [],
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}
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@ -67,12 +68,18 @@ def test_get_schedule_score_09_05(get_schedule_quality_response):
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assert response.status_code == status.HTTP_200_OK
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assert response.json() == {
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"total_score": 27,
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"total_score": 28,
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"comments": [
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{"type": "warning", "text": "Schedule has gaps"},
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{"type": "warning", "text": "Schedule has balance issues"},
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{"type": "warning", "text": "Schedule has gaps (79% not covered)"},
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{"type": "warning", "text": "Schedule has balance issues (see overloaded users)"},
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],
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"overloaded_users": [
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{
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"id": user1.public_primary_key,
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"username": user1.username,
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"score": 49,
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},
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],
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"overloaded_users": [user1.public_primary_key],
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}
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@ -84,10 +91,16 @@ def test_get_schedule_score_09_09(get_schedule_quality_response):
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assert response.json() == {
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"total_score": 51,
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"comments": [
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{"type": "warning", "text": "Schedule has gaps"},
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{"type": "info", "text": "Schedule is well-balanced, but still can be improved"},
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{"type": "warning", "text": "Schedule has gaps (81% not covered)"},
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{"type": "warning", "text": "Schedule has balance issues (see overloaded users)"},
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],
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"overloaded_users": [
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{
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"id": user2.public_primary_key,
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"username": user2.username,
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"score": 9,
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},
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],
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"overloaded_users": [user2.public_primary_key],
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}
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@ -113,8 +126,233 @@ def test_get_schedule_score_09_19(get_schedule_quality_response):
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assert response.json() == {
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"total_score": 70,
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"comments": [
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{"type": "warning", "text": "Schedule has gaps"},
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{"type": "warning", "text": "Schedule has gaps (59% not covered)"},
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{"type": "info", "text": "Schedule is perfectly balanced"},
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],
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"overloaded_users": [],
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}
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@pytest.mark.django_db
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def test_get_schedule_score_weekdays(
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make_organization,
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make_user_for_organization,
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make_token_for_organization,
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make_schedule,
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make_on_call_shift,
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make_user_auth_headers,
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):
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organization = make_organization()
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_, token = make_token_for_organization(organization)
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schedule = make_schedule(
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organization,
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schedule_class=OnCallScheduleWeb,
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name="test_quality",
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)
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|
||||
users = [make_user_for_organization(organization, username=f"user-{idx}") for idx in range(8)]
|
||||
# clear users pks <-> organization cache (persisting between tests)
|
||||
memoized_users_in_ical.cache_clear()
|
||||
|
||||
make_on_call_shift(
|
||||
schedule.organization,
|
||||
shift_type=CustomOnCallShift.TYPE_ROLLING_USERS_EVENT,
|
||||
schedule=schedule,
|
||||
start=datetime.datetime(2022, 3, 20, 0, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
duration=datetime.timedelta(hours=12),
|
||||
rotation_start=datetime.datetime(2022, 3, 20, 0, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
until=None,
|
||||
rolling_users=[{user.pk: user.public_primary_key for user in users[:4]}],
|
||||
frequency=CustomOnCallShift.FREQUENCY_WEEKLY,
|
||||
by_day=["MO", "TU", "WE", "TH", "FR"],
|
||||
)
|
||||
|
||||
make_on_call_shift(
|
||||
schedule.organization,
|
||||
shift_type=CustomOnCallShift.TYPE_ROLLING_USERS_EVENT,
|
||||
schedule=schedule,
|
||||
start=datetime.datetime(2022, 3, 20, 12, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
duration=datetime.timedelta(hours=12),
|
||||
rotation_start=datetime.datetime(2022, 3, 20, 12, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
until=None,
|
||||
rolling_users=[{user.pk: user.public_primary_key for user in users[4:]}],
|
||||
frequency=CustomOnCallShift.FREQUENCY_WEEKLY,
|
||||
by_day=["MO", "TU", "WE", "TH", "FR"],
|
||||
)
|
||||
|
||||
client = APIClient()
|
||||
|
||||
url = reverse("api-internal:schedule-quality", kwargs={"pk": schedule.public_primary_key}) + "?date=2022-03-24"
|
||||
response = client.get(url, **make_user_auth_headers(users[0], token))
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.json() == {
|
||||
"total_score": 86,
|
||||
"comments": [
|
||||
{"type": "warning", "text": "Schedule has gaps (29% not covered)"},
|
||||
{"type": "info", "text": "Schedule is perfectly balanced"},
|
||||
],
|
||||
"overloaded_users": [],
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_get_schedule_score_all_week(
|
||||
make_organization,
|
||||
make_user_for_organization,
|
||||
make_token_for_organization,
|
||||
make_schedule,
|
||||
make_on_call_shift,
|
||||
make_user_auth_headers,
|
||||
):
|
||||
organization = make_organization()
|
||||
_, token = make_token_for_organization(organization)
|
||||
|
||||
schedule = make_schedule(
|
||||
organization,
|
||||
schedule_class=OnCallScheduleWeb,
|
||||
name="test_quality",
|
||||
)
|
||||
|
||||
users = [make_user_for_organization(organization, username=f"user-{idx}") for idx in range(8)]
|
||||
# clear users pks <-> organization cache (persisting between tests)
|
||||
memoized_users_in_ical.cache_clear()
|
||||
|
||||
make_on_call_shift(
|
||||
schedule.organization,
|
||||
shift_type=CustomOnCallShift.TYPE_ROLLING_USERS_EVENT,
|
||||
schedule=schedule,
|
||||
start=datetime.datetime(2022, 3, 20, 0, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
duration=datetime.timedelta(hours=12),
|
||||
rotation_start=datetime.datetime(2022, 3, 20, 0, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
until=None,
|
||||
rolling_users=[{user.pk: user.public_primary_key for user in users[:4]}],
|
||||
frequency=CustomOnCallShift.FREQUENCY_WEEKLY,
|
||||
by_day=["MO", "TU", "WE", "TH", "FR"],
|
||||
)
|
||||
|
||||
make_on_call_shift(
|
||||
schedule.organization,
|
||||
shift_type=CustomOnCallShift.TYPE_ROLLING_USERS_EVENT,
|
||||
schedule=schedule,
|
||||
start=datetime.datetime(2022, 3, 20, 12, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
duration=datetime.timedelta(hours=12),
|
||||
rotation_start=datetime.datetime(2022, 3, 20, 12, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
until=None,
|
||||
rolling_users=[{user.pk: user.public_primary_key for user in users[4:]}],
|
||||
frequency=CustomOnCallShift.FREQUENCY_WEEKLY,
|
||||
by_day=["MO", "TU", "WE", "TH", "FR"],
|
||||
)
|
||||
|
||||
make_on_call_shift(
|
||||
schedule.organization,
|
||||
shift_type=CustomOnCallShift.TYPE_ROLLING_USERS_EVENT,
|
||||
schedule=schedule,
|
||||
start=datetime.datetime(2022, 3, 20, 12, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
duration=datetime.timedelta(hours=24),
|
||||
rotation_start=datetime.datetime(2022, 3, 20, 12, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
until=None,
|
||||
rolling_users=[{user.pk: user.public_primary_key for user in users}],
|
||||
frequency=CustomOnCallShift.FREQUENCY_WEEKLY,
|
||||
by_day=["SA", "SU"],
|
||||
)
|
||||
|
||||
client = APIClient()
|
||||
|
||||
url = reverse("api-internal:schedule-quality", kwargs={"pk": schedule.public_primary_key}) + "?date=2022-03-24"
|
||||
response = client.get(url, **make_user_auth_headers(users[0], token))
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.json() == {
|
||||
"total_score": 100,
|
||||
"comments": [
|
||||
{"type": "info", "text": "Schedule has no gaps"},
|
||||
{"type": "info", "text": "Schedule is perfectly balanced"},
|
||||
],
|
||||
"overloaded_users": [],
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_get_schedule_score_all_week_imbalanced_weekends(
|
||||
make_organization,
|
||||
make_user_for_organization,
|
||||
make_token_for_organization,
|
||||
make_schedule,
|
||||
make_on_call_shift,
|
||||
make_user_auth_headers,
|
||||
):
|
||||
organization = make_organization()
|
||||
_, token = make_token_for_organization(organization)
|
||||
|
||||
schedule = make_schedule(
|
||||
organization,
|
||||
schedule_class=OnCallScheduleWeb,
|
||||
name="test_quality",
|
||||
)
|
||||
|
||||
users = [make_user_for_organization(organization, username=f"user-{idx}") for idx in range(8)]
|
||||
# clear users pks <-> organization cache (persisting between tests)
|
||||
memoized_users_in_ical.cache_clear()
|
||||
|
||||
make_on_call_shift(
|
||||
schedule.organization,
|
||||
shift_type=CustomOnCallShift.TYPE_ROLLING_USERS_EVENT,
|
||||
schedule=schedule,
|
||||
start=datetime.datetime(2022, 3, 20, 0, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
duration=datetime.timedelta(hours=12),
|
||||
rotation_start=datetime.datetime(2022, 3, 20, 0, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
until=None,
|
||||
rolling_users=[{user.pk: user.public_primary_key for user in users[:4]}],
|
||||
frequency=CustomOnCallShift.FREQUENCY_WEEKLY,
|
||||
by_day=["MO", "TU", "WE", "TH", "FR"],
|
||||
)
|
||||
|
||||
make_on_call_shift(
|
||||
schedule.organization,
|
||||
shift_type=CustomOnCallShift.TYPE_ROLLING_USERS_EVENT,
|
||||
schedule=schedule,
|
||||
start=datetime.datetime(2022, 3, 20, 12, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
duration=datetime.timedelta(hours=12),
|
||||
rotation_start=datetime.datetime(2022, 3, 20, 12, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
until=None,
|
||||
rolling_users=[{user.pk: user.public_primary_key for user in users[4:]}],
|
||||
frequency=CustomOnCallShift.FREQUENCY_WEEKLY,
|
||||
by_day=["MO", "TU", "WE", "TH", "FR"],
|
||||
)
|
||||
|
||||
make_on_call_shift(
|
||||
schedule.organization,
|
||||
shift_type=CustomOnCallShift.TYPE_ROLLING_USERS_EVENT,
|
||||
schedule=schedule,
|
||||
start=datetime.datetime(2022, 3, 20, 12, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
duration=datetime.timedelta(hours=24),
|
||||
rotation_start=datetime.datetime(2022, 3, 20, 12, 0, 0, tzinfo=datetime.timezone.utc),
|
||||
until=None,
|
||||
rolling_users=[{user.pk: user.public_primary_key for user in users[:4]}],
|
||||
frequency=CustomOnCallShift.FREQUENCY_WEEKLY,
|
||||
by_day=["SA", "SU"],
|
||||
)
|
||||
|
||||
client = APIClient()
|
||||
|
||||
url = reverse("api-internal:schedule-quality", kwargs={"pk": schedule.public_primary_key}) + "?date=2022-03-24"
|
||||
response = client.get(url, **make_user_auth_headers(users[0], token))
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.json() == {
|
||||
"total_score": 88,
|
||||
"comments": [
|
||||
{"type": "info", "text": "Schedule has no gaps"},
|
||||
{"type": "warning", "text": "Schedule has balance issues (see overloaded users)"},
|
||||
],
|
||||
"overloaded_users": [
|
||||
{
|
||||
"id": user.public_primary_key,
|
||||
"username": user.username,
|
||||
"score": 29,
|
||||
}
|
||||
for user in users[:4]
|
||||
],
|
||||
}
|
||||
|
|
|
|||
19
grafana-plugin/integration-tests/schedules/quality.test.ts
Normal file
19
grafana-plugin/integration-tests/schedules/quality.test.ts
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
import { test, expect } from '@playwright/test';
|
||||
import { configureOnCallPlugin } from '../utils/configurePlugin';
|
||||
import { generateRandomValue } from '../utils/forms';
|
||||
import { createOnCallSchedule } from '../utils/schedule';
|
||||
|
||||
test.beforeEach(async ({ page }) => {
|
||||
await configureOnCallPlugin(page);
|
||||
});
|
||||
|
||||
test('check schedule quality for simple 1-user schedule', async ({ page }) => {
|
||||
const onCallScheduleName = generateRandomValue();
|
||||
await createOnCallSchedule(page, onCallScheduleName);
|
||||
|
||||
await expect(page.locator('div[class*="ScheduleQuality"]')).toHaveText('Quality: Great');
|
||||
|
||||
await page.hover('div[class*="ScheduleQuality"]');
|
||||
await expect(page.locator('div[class*="ScheduleQualityDetails"] >> span[class*="Text"] >> nth=2 ')).toHaveText('Schedule has no gaps');
|
||||
await expect(page.locator('div[class*="ScheduleQualityDetails"] >> span[class*="Text"] >> nth=3 ')).toHaveText('Schedule is perfectly balanced');
|
||||
});
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
$padding: 8px;
|
||||
$width: 280px;
|
||||
$width: 340px;
|
||||
|
||||
.root {
|
||||
width: $width;
|
||||
|
|
@ -53,7 +53,7 @@ $width: 280px;
|
|||
padding-left: 24px;
|
||||
}
|
||||
|
||||
.email {
|
||||
.username {
|
||||
max-width: calc($width - $padding);
|
||||
white-space: nowrap;
|
||||
text-overflow: ellipsis;
|
||||
|
|
|
|||
|
|
@ -1,14 +1,10 @@
|
|||
import React, { FC, useCallback, useEffect, useState } from 'react';
|
||||
import React, { FC, useCallback, useState } from 'react';
|
||||
|
||||
import { HorizontalGroup, Icon, IconButton } from '@grafana/ui';
|
||||
import cn from 'classnames/bind';
|
||||
import dayjs from 'dayjs';
|
||||
|
||||
import Text from 'components/Text/Text';
|
||||
import { ScheduleScoreQualityResponse, ScheduleScoreQualityResult } from 'models/schedule/schedule.types';
|
||||
import { getTzOffsetString } from 'models/timezone/timezone.helpers';
|
||||
import { User } from 'models/user/user.types';
|
||||
import { useStore } from 'state/useStore';
|
||||
import { getVar } from 'utils/DOM';
|
||||
|
||||
import styles from './ScheduleQualityDetails.module.scss';
|
||||
|
|
@ -22,24 +18,13 @@ interface ScheduleQualityDetailsProps {
|
|||
}
|
||||
|
||||
export const ScheduleQualityDetails: FC<ScheduleQualityDetailsProps> = ({ quality, getScheduleQualityString }) => {
|
||||
const { userStore } = useStore();
|
||||
const { total_score: score, comments, overloaded_users } = quality;
|
||||
const [expanded, setExpanded] = useState<boolean>(false);
|
||||
const [isLoading, setIsLoading] = useState<boolean>(true);
|
||||
const [overloadedUsers, setOverloadedUsers] = useState<User[]>([]);
|
||||
|
||||
useEffect(() => {
|
||||
fetchUsers();
|
||||
}, []);
|
||||
|
||||
const handleExpandClick = useCallback(() => {
|
||||
setExpanded((expanded) => !expanded);
|
||||
}, []);
|
||||
|
||||
if (isLoading) {
|
||||
return null;
|
||||
}
|
||||
|
||||
const infoComments = comments.filter((c) => c.type === 'info');
|
||||
const warningComments = comments.filter((c) => c.type === 'warning');
|
||||
|
||||
|
|
@ -94,15 +79,15 @@ export const ScheduleQualityDetails: FC<ScheduleQualityDetailsProps> = ({ qualit
|
|||
</>
|
||||
)}
|
||||
|
||||
{overloadedUsers?.length > 0 && (
|
||||
{overloaded_users?.length > 0 && (
|
||||
<div className={cx('container')}>
|
||||
<div className={cx('row')}>
|
||||
<Icon name="users-alt" />
|
||||
<div className={cx('container')}>
|
||||
<Text type="secondary">Overloaded users</Text>
|
||||
{overloadedUsers.map((overloadedUser, index) => (
|
||||
<Text type="primary" className={cx('email')} key={index}>
|
||||
{overloadedUser.email} ({getTzOffsetString(dayjs().tz(overloadedUser.timezone))})
|
||||
{overloaded_users.map((overloadedUser, index) => (
|
||||
<Text type="primary" className={cx('username')} key={index}>
|
||||
{overloadedUser.username} (+{overloadedUser.score}% avg)
|
||||
</Text>
|
||||
))}
|
||||
</div>
|
||||
|
|
@ -125,7 +110,7 @@ export const ScheduleQualityDetails: FC<ScheduleQualityDetailsProps> = ({ qualit
|
|||
</HorizontalGroup>
|
||||
{expanded && (
|
||||
<Text type="primary" className={cx('text')}>
|
||||
The next 90 days are taken into consideration when calculating the overall schedule quality.
|
||||
The next 52 weeks are taken into consideration when calculating the overall schedule quality.
|
||||
</Text>
|
||||
)}
|
||||
</div>
|
||||
|
|
@ -133,25 +118,6 @@ export const ScheduleQualityDetails: FC<ScheduleQualityDetailsProps> = ({ qualit
|
|||
</div>
|
||||
);
|
||||
|
||||
async function fetchUsers() {
|
||||
if (!overloaded_users?.length) {
|
||||
setIsLoading(false);
|
||||
return;
|
||||
}
|
||||
|
||||
const allUsersList: User[] = userStore.getSearchResult().results;
|
||||
const overloadedUsers = [];
|
||||
|
||||
allUsersList.forEach((user) => {
|
||||
if (overloaded_users.indexOf(user['pk']) !== -1) {
|
||||
overloadedUsers.push(user);
|
||||
}
|
||||
});
|
||||
|
||||
setIsLoading(false);
|
||||
setOverloadedUsers(overloadedUsers);
|
||||
}
|
||||
|
||||
function getScheduleQualityMatchingColor(score: number): string {
|
||||
if (score < 20) {
|
||||
return getVar('--tag-text-danger');
|
||||
|
|
|
|||
|
|
@ -188,8 +188,7 @@ export class ScheduleStore extends BaseStore {
|
|||
}
|
||||
|
||||
async getScoreQuality(scheduleId: Schedule['id']): Promise<ScheduleScoreQualityResponse> {
|
||||
const tomorrow = getFromString(dayjs().add(1, 'day'));
|
||||
return await makeRequest(`/schedules/${scheduleId}/quality?date=${tomorrow}`, { method: 'GET' });
|
||||
return await makeRequest(`/schedules/${scheduleId}/quality`, { method: 'GET' });
|
||||
}
|
||||
|
||||
@action
|
||||
|
|
|
|||
|
|
@ -115,7 +115,7 @@ export interface ShiftEvents {
|
|||
export interface ScheduleScoreQualityResponse {
|
||||
total_score: number;
|
||||
comments: Array<{ type: 'warning' | 'info'; text: string }>;
|
||||
overloaded_users: string[];
|
||||
overloaded_users: Array<{ id: string; username: string; score: number }>;
|
||||
}
|
||||
|
||||
export enum ScheduleScoreQualityResult {
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue